Building tomography: Automatic floor plan generation for indoor localization

Indoor localization is of great importance for a range of pervasive applications, attracting many research eorts in the past decades. Most radio-based solutions require 1) priori knowledge of buildings, usually represented as a floor plan and 2) a process of site survey, in which radio signatures of an interested area are annotated with their real recorded locations. Floor plan plays an essential role in many indoor pervasive and mobile applications, but its collection and on-site calibration are inconvenient and usually prohibitively costly for map providers. Site survey involves intensive costs on manpower and time.;In this study, we investigate novel sensors integrated in modern mobile phones and leverage user motions to release the human efforts in constructing the floor map of a building. We propose Building Tomography, which automatically explores indoor architectural layouts and samples radio fingerprints. Building Tomography generates a floor plan illustrating a number of key spatial elements like rooms, corridors, walls, and other physical features at one level of a building, and constructs corresponding radio map towards it. Our idea is based on human-centric sensing and crowdsourcing. The popularity of smartphones, with rich built-in sensors, enables fine-grained sensory records on human mobility and activity. Although the records from one user might be less useful, a large amount of contributing users enrich the records to an applicable level so that the interior layout of a building emerges.;Our main contribution is to design and implement a building tomography system that is inexpensive and pervasive. No building knowledge is required and all sensor readings are collected by off-the-shelf smartphones. To validate this design, we deploy a prototype system and conduct experiments in an office building. Results show that the generated floor plan accurately reflects real layout and is able to facilitate many pervasive applications, including indoor localization and navigation.;To put the building tomography system into practice, we also address location privacy issues in wireless and mobile networks by proposing Adhoc Anonymity location privacy preservation scheme. Adhoc Anonymity works for self-centered users and in the absence of intermediary, and thus well fits the task of protecting user privacy in crowdsourcing. To demonstrate the importance of location and localization, we also conduct a case study of localization application in mobile networks. ReC is a VANET protocol that utilizes location information to enhance geocasting efficiency and reliability.